Heterogeneous　multi-core　processors　have　become　the　forefront　of　processor　development　due　to　their　advantages　in　system　throughput　and　execution　efficiency,　but　they　also　bring　many　new　challenges　to　system　design.　The　mapping　of　heterogeneous　Network-on-Chip　(NoC)　is　challenging.　To　solve　this　problem,　this　paper　proposes　a　heterogeneous　multi-core　processor　task　mapping　algorithm　based　on　an　improved　genetic　algorithm.　By　constructing　a　good　initial　population　method　to　improve　the　initial　population　quality,　a　dual　population　genetic　mechanism　is　used　in　the　iteration　process.　The　algorithm　can　make　tasks　more　reasonably　distributed　to　various　network　nodes,　and　has　high　efficiency　for　optimizing　network　power　consumption　on　heterogeneous　multi-cores.　©　2019　Institute　of　Physics　Publishing.　All　rights　reserved.